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quant-ph2025

Opportunities and Challenges for Data Quality in the Era of Quantum Computing

Sven Groppe, Valter Uotila, Jinghua Groppe

In an era where data underpins decision-making across science, politics, and economics, ensuring high data quality is of paramount importance. Conventional computing algorithms for…

quant-ph2025

Higher-Order Portfolio Optimization with Quantum Approximate Optimization Algorithm

Valter Uotila, Julia Ripatti, Bo Zhao

Portfolio optimization is one of the most studied optimization problems at the intersection of quantum computing and finance. In this work, we develop the first quantum formulation…

quant-ph2025

Agent-Q: Fine-Tuning Large Language Models for Quantum Circuit Generation and Optimization

Linus Jern, Valter Uotila, Cong Yu +1

Large language models (LLMs) have achieved remarkable outcomes in complex problems, including math, coding, and analyzing large amounts of scientific reports. Yet, few works have e…

quant-ph2025

Quantum Information-Theoretical Size Bounds for Conjunctive Queries with Functional Dependencies

Valter Uotila, Jiaheng Lu

Deriving formulations to estimate worst-case size bounds for conjunctive queries under various constraints has been at the core of theoretical database research. If the problem has…

quant-ph2025

Left-Deep Join Order Selection with Higher-Order Unconstrained Binary Optimization on Quantum Computers

Valter Uotila

Join order optimization is among the most crucial query optimization problems, and its central position is also evident in the new research field where quantum computing is applied…

quant-ph2024

QCE'24 Tutorial: Quantum Annealing -- Emerging Exploration for Database Optimization

Nitin Nayak, Manuel Schönberger, Valter Uotila +4

Quantum annealing is a meta-heuristic approach tailored to solve combinatorial optimization problems with quantum annealers. In this tutorial, we provide a fundamental and comprehe…